Back Flips with a Hexapedal Robot

We report on the design and analysis of a controller which can achieve dynamical self-righting of our hexapedal robot, RHex. We present an empirically developed control procedure which works reasonably well on indoor surfaces, using a hybrid energy pumping strategy to overcome torque limitations of its actuators. Subsequent modeling and analysis yields a new controller with a much wider domain of success as well as a preliminary understanding of the necessary hybrid control strategy. Simulation results demonstrate the superiority of the improved control strategy to the first generation empirically designed controller

Template Based Control of Hexapedal Running

In this paper, we introduce a hexapedal locomotion controller that simulation evidence suggests will be capable of driving our RHex robot at speeds exceeding five body lengths per second with reliable stability and rapid maneuverability. We use a low dimensional passively compliant biped as a template -- a control target for the alternating tripod gait of the physical machine. We impose upon the physical machine an approrimate inverse dynamics within-stride controller designed to force the true high dimensional system dynamics down onto the lower dimensional subspace corresponding to the template. Numerical simulations suggest the presence of asymptotically stable mnning gaits with large basins of attraction. Moreover, this controller improves substantially the maneuverability and dynamic range of RHex\u27s running behaviors relative to the initial prototype open-loop algorithms

A Real-time Inertial Motion Blur Metric

Mobile robots suffer from sensor data corruption due to body oscillations and disturbances. Especially, information loss on images captured with onboard cameras can be extremely high and such loss may become irreversible or deblurring can be computationally costly. In this paper, a novel method is proposed to minimize average motion blur captured by mobile cameras. A real-time computable motion blur metric (MMBM) is derived by using only inertial sensor measurements. MMBM is validated by comparing it to optic flow results. To express the applicability of MMBM, a motion blur minimizing system is built on the RHex. To this end, an onboard camera is externally triggered depending on the real-time-calculated MMBM while the robot is walking straight on a flat surface. The resulting motion blur is compared to motion blur levels of a regular, fixed frame-rate image acquisition schedule by qualitative inspection on captured images

A Real-time Inertial Motion Blur Metric: Application to Frame Triggering Based Motion Blur Minimization

Mobile robots suffer from sensory data corruption due to body oscillations and disturbances. In particular, information loss on images captured with onboard cameras can be very high, and such loss may become irreversible or computationally costly to undo. In this paper, we propose a novel method to minimize average motion blur captured by such mobile visual sensors. To this end, we derive a motion blur metric (MMBM) that can be computed in real-time by using only inertial sensor measurements and validate it through comparisons with optic flow computations. The applicability of MMBM is illustrated through a motion blur minimizing system implemented on the SensoRHex hexapod robot by externally triggering an onboard camera based on MMBM values computed in real-time while the robot is walking straight on a flat surface. The resulting motion blur is compared to motion blur levels obtained with a regular, fixed frame-rate image acquisition schedule by both qualitative inspection and using a blind blur metric on captured images. MMBM based motion blur minimization system not only reduces average motion blur, but also avoids frames with extreme motion blur before an image gets corrupted by appropriately delaying the triggering of frame acquisition

Extending The Lossy Spring-Loaded Inverted Pendulum Model with a Slider-Crank Mechanism

Spring Loaded Inverted Pendulum (SLIP) model has a long history in describing running behavior in animals and humans as well as has been used as a design basis for robots capable of dynamic locomotion. Anchoring the SLIP for lossy physical systems resulted in newer models which are extended versions of original SLIP with viscous damping in the leg. However, such lossy models require an additional mechanism for pumping energy to the system to control the locomotion and to reach a limit-cycle. Some studies solved this problem by adding an actively controllable torque actuation at the hip joint and this actuation has been successively used in many robotic platforms, such as the popular RHex robot. However, hip torque actuation produces forces on the COM dominantly at forward direction with respect to ground, making height control challenging especially at slow speeds. The situation becomes more severe when the horizontal speed of the robot reaches zero, i.e. steady hoping without moving in horizontal direction, and the system reaches to singularity in which vertical degrees of freedom is completely lost. To this end, we propose an extension of the lossy SLIP model with a slider-crank mechanism, SLIP- SCM, that can generate a stable limit-cycle when the body is constrained to vertical direction. We propose an approximate analytical solution to the nonlinear system dynamics of SLIP- SCM model to characterize its behavior during the locomotion. Finally, we perform a fixed-point stability analysis on SLIP-SCM model using our approximate analytical solution and show that proposed model exhibits stable behavior in our range of interest.Comment: To appear in The 17th International Conference on Advanced Robotic

Model-Based Dynamic Self-Righting Maneuvers for a Hexapedal Robot

We report on the design and analysis of a controller that can achieve dynamical self-righting of our hexapedal robot, RHex. Motivated by the initial success of an empirically tuned controller, we present a feedback controller based on a saggital plane model of the robot. We also extend this controller to develop a hybrid pumping strategy that overcomes actuator torque limitations, resulting in robust flipping behavior over a wide range of surfaces. We present simulations and experiments to validate the model and characterize the performance of the new controller

Proprioception Based Behavioral Advances in a Hexapod Robot

We report on our progress in extending the behavioral repertoire of RHex, a compliant leg hexapod robot. We introduce two new controllers, one for climbing constant slope inclinations and one for achieving higher speeds via pronking, a gait that incorporates a, substantial aerial phase. In both cases, we make use of an underlying open-loop control strategy, combined with low bandwidth feedback to modulate its parameters. The inclination behavior arises from our initial alternating tripod walking controller and adjusts the angle offsets of individual leg motion profiles based on inertial sensing of the average surface slope. Similarly, the pronking controller makes use of a virtual leg touchdown sensing mechanism to adjust the frequency of the open-loop pronking, effectively synchronizing the controller with the natural oscillations of the mechanical system. Experimental results demonstrate good performance on slopes inclined up to /spl sim/250 and pronking up to speeds approaching 2 body lengths per second (/spl sim/1.0 m/s)

Dynamic locomotion with a hexapod robot.

Legged vehicles offer superior mobility over natural terrain compared to traditional mobile platforms. Furthermore, their structural flexibility admits greater versatility in functionality. This thesis concerns the development of dynamically capable controllers for a hexapedal robot in order to achieve fast, agile and efficient locomotion. The first contribution towards this end is the design and construction of a hexapedal robot, RHex. The experimental results we present establish RHex as the first power autonomous robot to achieve speeds exceeding one body length per second over terrain approaching the complexity and diversity of the natural landscape. The combination of simple open-loop control algorithms and RHex's morphology exploits mechanical feedback to yield surprising energetic performance and robustness. Furthermore, the versatility of the design becomes evident in additional behaviors that we present, including turning and dynamical back-flips. The second contribution of this thesis is the development of high bandwidth state feedback controller for hexapedal locomotion. This approach lies in extreme opposition to our open-loop controllers and is inspired by the dynamical nature of running in animals. In particular, research in biomechanics demonstrates the descriptive utility of simple spring mass models across a large range of sizes and morphologies. Consequently, we adopt the well studied Spring-Loaded Inverted Pendulum (SLIP) model as a literal control target for a hexapedal alternating tripod gait. Now the design effort focuses on speed and agility, with the possibility that such high bandwidth sensor feedback may be rather costly to implement regarding both platform resources as well as runtime efficiency. Specifically, we introduce the idea of template based control , wherein we attempt to actively tune the natural dynamics of the robot to mimic those of SLIP. We use existing gait level SLIP controllers to achieve stable locomotion in simulation, with a simple and intuitive regulatory interface. Despite realistic actuation constraints, we identify stable limit cycles with large basins of attraction, significantly increasing the promise for an experimental implementation on RHex. Even though such an implementation is outside the scope of the thesis, only a few practical issues remain to be resolved before it becomes a reality.Ph.D.Applied SciencesArtificial intelligenceComputer scienceMechanicsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/123265/2/3068951.pd

Template Based Control of Hexapedal Running

In this paper, we introduce a hexapedal locomotion controller that simulation evidence suggests will be capable of driving our RHex robot at speeds exceeding five body lengths per second with reliable stability and rapid maneuverability. We use a low dimensional passively compliant biped as a “template ” — a control target for the alternating tripod gait of the physical machine. We impose upon the physical machine an approximate inverse dynamics within-stride controller designed to force the true high dimensional system dynamics down onto the lower dimensional subspace corresponding to the template. Numerical simulations suggest the presence of asymptotically stable running gaits with large basins of attraction. Moreover, this controller improves substantially the maneuverability and dynamic range of RHex’s running behaviors relative to the initial prototype open-loop algorithms